Title :
Exploring chaos automata for protein sequences
Author :
Stoffer, Deborah A. ; Volkert, L. Gwenn
Author_Institution :
Dept. of Comput. Sci., Kent State Univ., Kent, OH
Abstract :
Fractals have been used to visually represent biological sequences since 1990. At first simple chaos games were used to generate fractal visualizations for DNA sequences, but the technique developed into using more complex systems to visually represent DNA and protein sequences. One of these more complex systems, termed chaos automata, combined iterated function systems with finite state automata to retain a memory of sequence input. The parameters for chaos automata were evolved by evolutionary algorithm to distinguish between different properties in DNA sequence input. Here, chaos automata have been extended to protein sequences and explored using synthetic protein sequence data.
Keywords :
automata theory; bioinformatics; biological techniques; data visualisation; evolutionary computation; finite state machines; iterative methods; proteins; proteomics; DNA sequence input; DNA sequences; biological sequence visual representation; chaos automata; evolutionary algorithm; finite state automata; fractals; iterated function systems; protein sequences; sequence input memory; Automata; Chaos; DNA; Data visualization; Evolutionary computation; Fractals; Gaskets; Image generation; Protein engineering; Protein sequence;
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology, 2008. CIBCB '08. IEEE Symposium on
Conference_Location :
Sun Valley, ID
Print_ISBN :
978-1-4244-1778-0
Electronic_ISBN :
978-1-4244-1779-7
DOI :
10.1109/CIBCB.2008.4675757
